Knowledge Hut

JANUARY 22, 2024

Some common specializations include: Machine Learning and AI These courses provide in-depth knowledge of machine learning algorithms like regression, classification, clustering, deep learning and natural language processing. Students work with SQL, NoSQL databases, Hadoop ecosystem, Spark, Kafka etc.

Data Science 52

Data Science Certification Education Data Lake 52

ProjectPro

NOVEMBER 24, 2021

Knowledge of machine learning algorithms and deep learning algorithms. Experience with Big data tools like Hadoop, Spark, etc. Recommended Reading: 50 ML Projects To Strengthen Your Portfolio and Get You Hired FAQs on Learning Data Science Is data science a hard job? Strong programming skills.

Data Science 52

Data Science Consulting Machine Learning Software Engineer 52

ProjectPro

APRIL 17, 2015

This articles explores four latest trends in big data analytics that are driving implementation of cutting edge technologies like Hadoop and NoSQL. Let’s hope for some innovative hit in deep learning to real time business situations by end of 2015.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 52

ProjectPro

JULY 23, 2021

Orchestrate Redshift ETL using AWS Glue and Step Functions AWS Projects for Portfolio 17. Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects. Ace your Big Data engineer interview by working on unique end-to-end solved Big Data Projects using Hadoop. Serverless Image Recognition Engine 13.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

Databand.ai

DECEMBER 13, 2022

He also has more than 10 years of experience in big data, being among the few data engineers to work on Hadoop Big Data Analytics prior to the adoption of public cloud providers like AWS, Azure, and Google Cloud Platform. On LinkedIn, he focuses largely on Spark, Hadoop, big data, big data engineering, and data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

DECEMBER 26, 2023

Following an MBA in finance, the best career options after BCom include those as a finance manager, consultant, financial analyst, credit risk manager , portfolio manager, and treasurer. You can work at managerial levels in finance, BFSI, FMCG, IT, consulting, and top companies after earning an MBA in finance.

Banking 52

Banking Insurance Finance Cloud Computing 52

ProjectPro

FEBRUARY 24, 2016

These companies are looking to hire the brightest professionals with expertise in Math, Statistics, SQL, Hadoop, Java, Python, and R skills for their own data science teams. A data scientist must have in-depth knowledge of technologies used to tame big data and should always be willing to learn the merging ones. Computer Science vs.

Hadoop 40

Hadoop Data Science Computer Science R (Programming) 40

ProjectPro

JULY 28, 2021

Can you explain the Hadoop architecture? To increase your chances of getting hired as a data scientist at Google, you must work on building a portfolio of projects that demonstrate your technical skills and non-technical skills to create a lasting impact on the recruiting panel.

Recruitment 40

Recruitment Data Science Machine Learning NoSQL 40

ProjectPro

AUGUST 24, 2021

Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects 1) Smart IoT Infrastructure In this IoT project , you will be discussing a general architecture for building smart IoT infrastructure. Learn how to process Wikipedia archives using Hadoop and identify the lived pages in a day.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. Big Deal Companies are striking with Big Data Analytics What is Hadoop?

Hadoop 52

Hadoop Big Data Unstructured Data Retail 52

ProjectPro

SEPTEMBER 26, 2021

Hadoop , Kafka , and Spark are the most popular big data tools used in the industry today. Prior learning and knowledge of these tools will distinguish you from the rest of the candidates. You will get to learn about data storage and management with lessons on Big Data tools. Hadoop, for instance, is open-source software.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 18, 2024

The insights that are generated through this process of Data Science can enable businesses to identify new opportunities, increase operational efficiency and effectiveness, improve their current strategies to grow their portfolio, and strengthen their position in the market. SQL for data migration 2.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

ProjectPro

MARCH 12, 2016

How PayPal uses Hadoop? Before the advent of Hadoop, PayPal just let all the data go, as it was difficult to catch-all schema types on traditional databases. Now, PayPal processes everything just through Hadoop and HBase - regardless of the data format. PayPal expands its Hadoop usage into HBase to leverage HDFS.

Big Data 52

Big Data Data Analytics Hadoop Algorithm 52

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

FEBRUARY 8, 2017

2017 will see a continuation of these big data trends as technology becomes smarter with the implementation of deep learning and AI by many organizations. Growing adoption of Artificial Intelligence, growth of IoT applications and increased adoption of machine learning will be the key to success for data-driven organizations in 2017.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

OCTOBER 27, 2021

The banking and finance industry generates enormous amounts of data related to transactions, billing, and payments from customers, which can provide accurate insights and predictions to be fed to machine learning models. There is a wide range of open-source machine learning algorithms and tools that fit exceptionally with financial data.

Finance 52

Finance Machine Learning Project Banking 52

ProjectPro

JANUARY 24, 2023

Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects Let us now explore the SageMaker architecture to understand what makes Amazon SageMaker unique and popular among the masses. Once data is prepared, the next step is building machine learning models and training them.

Building 52

Building Algorithm Machine Learning AWS 52

ProjectPro

DECEMBER 22, 2016

If you are aspiring to be a data analyst then the core competencies that you should be familiar with are distributed computing frameworks like Hadoop and Spark, knowledge of programming languages like Python, R , SAS, data munging, data visualization, math , statistics , and machine learning. How to create a sparse Matrix in Python?

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

ProjectPro

JANUARY 25, 2022

PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. Different machine learning and graph libraries are available in PySpark, and it is compatible with multiple cluster managers (Spark, Yarn, Mesos, etc.). When it comes to data ingestion pipelines, PySpark has a lot of advantages.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

NOVEMBER 30, 2021

When working on real-time business problems, data scientists build models using various Machine Learning or Deep Learning algorithms. Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects ETL Pipeline Tutorial - How to Build an ETL Pipeline?

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

SEPTEMBER 6, 2021

AWS vs. Google Cloud - Machine Learning AWS and GCP offer cutting-edge machine learning tools from their portfolio that help develop, train, and test a machine learning model. Tensorflow: Tensorflow is an already renowned name in the machine learning community.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

JANUARY 31, 2022

Snowflake is not based on existing database systems or big data software platforms like Hadoop. Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. Before actually working on any big data projects, data engineers must acquire proficient knowledge in the relevant areas, such as deep learning, machine learning, data visualization, data analytics, etc.

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

DECEMBER 15, 2021

The software will make this choice itself, picking from the existing portfolio of options the one fitting your task best. The accuracy of the forecast depends not only on features but also on hyperparameters or internal settings that dictate how exactly your algorithm will learn on a specific dataset. Algorithm selection.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59